Method and apparatus for combining range information with an optical image

ABSTRACT

A method for combining range information with an optical image is provided. The method includes capturing a first optical image of a scene with an optical camera, wherein the first optical image comprising a plurality of pixels. Additionally, range information of the scene is captured with a ranging device. Range values are then determined for at least a portion of the plurality of pixels of the first optical image based on the range information. The range values and the optical image are combined to produce a 3-dimensional (3D) point cloud. A second optical image of the scene from a different perspective than the first optical image is produced based on the 3D point cloud.

BACKGROUND

Currently there are devices that capture range information for a scene.One example of such a device is a light detection and ranging (LIDAR)device. LIDAR devices are sometimes referred to in the art as laserdetection and ranging (LADAR) devices, although both acronyms refer tothe same device. A LIDAR captures range information for a scene byemitting a flash of coherent light and measuring the amount of time ittakes the coherent light to travel from the LIDAR to objects within thefield of view of the LIDAR and back to the LIDAR. This is known as aflash LIDAR. Another type of LIDAR is a scanning LIDAR where a singlebeam of light is scanned across a scene. In either case, the LIDARreturns packets of timing information which may then be compiled into amatrix (referred to herein as a range matrix). Each data point of therange matrix corresponds to the amount of time taken by the coherentlight to bounce off of an object located at that data point. The rangematrix produced from the output of the LIDAR is a 2-dimensional map ofthe range information received.

Many devices also exist that capture optical information for a scene.One of the most common examples of a device that captures opticalinformation is a traditional camera. Cameras capture optical informationin the form of a 2-dimensional map of the optical information receivedat the camera from within the field of view of the camera. For example,a visual spectrum optical camera captures and records light within thevisual spectrum that reflects off of objects within the field of view ofthe camera.

Visual spectrum optical cameras have been used to create stereo visionsystems in an attempt to better replicate the human vision experience ofviewing the world from two perspectives (a left and a right eye). Imagesor videos created in this manner are sometimes referred to as3-dimensional (3D) images or videos. These 3D optical images are basedon taking two 2D optical images of a single scene from two differentperspectives. One optical image is taken from a perspective of a lefteye and the other image is taken from a perspective of a right eye. Atypical 3D camera consists of two lenses which are spaced apart atapproximately the distance of a human's eyes. The 3D camera takes two 2Dimages simultaneously, one with the left lens and one with the rightlens.

Special techniques are used to display the two images on a single screenand to give the viewer the impression that the left eye is viewing oneimage and the right eye is viewing the other image. For example, onemethod of viewing the two images requires the viewer to wear glasseshaving one red colored lens and one blue colored lens. Then the left eyeimage is shown in blue simultaneous with right eye image which is shownin red. With the glasses on, the viewer's left eye picks up on the leftblue images and the viewer's right eye picks up on the right red images.The viewer's brain then puts them together to create the real life 3Deffect. This effect can be used in either a still photograph or a videosetting.

Another method of viewing 3D images is similar except that instead ofred and blue images for the left and right eye, polarized images areused. Here, the left images are polarized in one direction and the rightimages are polarized at a 90 degree angle from the left images. The userthen wears glasses with a left lens matching the polarization of theleft image and a right lens matching the polarization of the rightimage.

A third method for viewing 3D videos involves alternating the left andright images from the camera on the viewing screen. Here, the viewer'sbrain forms the alternating images into a 3D image.

SUMMARY

The following summary is made by way of example and not by way oflimitation. In one embodiment, a method for combining range informationwith an optical image is provided. The method includes capturing a firstoptical image of a scene with an optical camera, wherein the firstoptical image comprising a plurality of pixels. Additionally, rangeinformation of the scene is captured with a ranging device. Range valuesare then determined for at least a portion of the plurality of pixels ofthe first optical image based on the range information. The range valuesand the optical image are combined to produce a 3-dimensional (3D) pointcloud. A second optical image of the scene from a different perspectivethan the first optical image is produced based on the 3D point cloud.

DRAWINGS

FIG. 1 is a block diagram of one embodiment of an imaging system forcombining an optical image and range information;

FIG. 2 is a flow chart of one embodiment of a method for combining anoptical image and range information using the imaging system of FIG. 1.

FIG. 3A is a flow chart of one embodiment of a method for using thecombination of the optical image and range information from FIG. 2;

FIG. 3B is a flow chart of another embodiment of a method for using thecombination of the optical image and range information from FIG. 2

FIG. 4A is an illustration of using the imaging system of FIG. 1 at afirst perspective with respect to a scene and an optical image resultingfrom this first perspective; and

FIG. 4B is an illustration of using the imaging system of FIG. 1 at asecond perspective with respect to the scene and a hypothetical opticalimage resulting from this second perspective.

DETAILED DESCRIPTION

FIG. 1 is one embodiment of a system 100 for combining an optical imagewith range information. System 100 includes a 2-dimensional (2D) opticalcamera 102, a ranging device 104, and a processing system 106.

Optical camera 102 captures a 2D optical image of a scene 108 which isin the field of view of camera 102. Optical camera 102 may capture scene108 as a black and white, grayscale, full color or other type of image.Additionally, optical camera 102 may have any resolution as desired fora particular application. Optical camera 102 captures opticalinformation in the form of a 2-dimensional map of the opticalinformation received at optical camera 102 from within the field of viewof optical camera 102. In this embodiment, optical camera 102 is avisual spectrum optical camera that captures and records light withinthe visual spectrum that reflects off of objects within the field ofview of optical camera 102. In one embodiment, optical camera 102 is astill camera that captures still images of a scene. In anotherembodiment, optical camera 102 is a video camera which captures multipleimages over time in a frame-by-frame manner to produce a video.

Ranging device 104 captures range information for the field of view ofranging device 104. In one embodiment ranging device 104 is a lightdetection and ranging (LIDAR) device. One form of a LIDAR captures rangeinformation for a scene by emitting a flash of coherent light andmeasuring the amount of time it takes the coherent light to travel fromthe LIDAR to objects within the field of view of the LIDAR and back tothe LIDAR. This is known as a flash LIDAR. Another type of LIDAR is ascanning LIDAR where a single beam of light is scanned across a scene.As mentioned in the background section, LIDAR devices are also referredto in the art as laser detection and ranging (LADAR) devices. In otherembodiments, ranging device 104 is a radio detection and scanning(RADAR) device, a sound and navigation ranging (SONAR) device, a time offlight camera, and a DOPPLER based device.

In either case, ranging device 104 returns packets of timing informationwhich may then be compiled into a matrix of range information (referredto herein as a range matrix). Each data point of the range matrixcorresponds to the amount of time taken by the coherent light to bounceoff of an object aligned with the pixel. The range matrix produced fromthe output of the ranging device 104 is a 2-dimensional map of the rangeinformation received for each pixel. In addition to the rangeinformation, ranging device 104 also captures an intensity matrix forthe field of view of ranging device 104. The intensity matrix representsa measure of the intensity of the coherent light received at rangingdevice 104 within each data point across the field of view. Similar tothe range information, the intensity information captured by rangingdevice 104 is compiled in the form of a matrix of intensity informationof information across the field of view.

Processing system 106 includes at least one programmable processor(referred to herein as “processor”) and at least one storage medium thatis communicatively coupled to the processor. In one embodiment, theprocessor comprises a microprocessor. The processor executes variousitems of software. The software comprises program instructions that areembodied on one or more items of processor-readable media. For example,processor readable media includes the at least one storage medium whichmay comprise a hard disk drive or other mass storage device local toprocessing system 106 and/or shared media such as a file server that isaccessed over a network such as a local area network or wide areanetwork such as the Internet. In one embodiment, the software isfirmware which is embedded in the storage medium within the processor.Optical camera 102 and ranging device 104 are communicatively coupled toprocessing system 106. Processing system 106 receives optical image datafrom optical camera 102 as well as intensity and/or range matrix datafrom ranging device 104. Processing system 106 then outputs a renderedimage or image data to a display 110.

Optical camera 102 and ranging device 104 are oriented such that atleast a portion of the field of view of each device overlaps. In oneembodiment, optical camera 102 and ranging device 104 are aligned suchthat the field of view of each device is substantially the same.Further, in one embodiment, optical camera 102 and ranging device 104are mounted in a fixed relationship to one another such that the fieldof view of each device remains the same relative to the other device.

FIG. 2 illustrates one embodiment of a method 200 of combining rangeinformation with an optical image using system 100. Method 200 begins atblock 202 where a 2D optical image of scene 108 is captured by opticalcamera 102. At block 204, range information for scene 108 is captured byranging device 104. When scene 108 contains moving objects, the opticalimage and the range information are captured at the same time to ensurethat the moving objects are captured in the same position in both theoptical image and the range information. When scene 108 contains onlynon-moving objects, the optical image and the range information may becaptured at different times. The optical image comprises a plurality ofpixels, each pixel comprising data representing the color or shade ofscene 108 at a position within the field of view of optical camera 102.As described above, the range information from ranging device 104 is inthe form of a range matrix that comprises a plurality of data points.Each data point of the range matrix represents range information forscene 108 within the field of view of ranging device 104.

At block 206 range values are determined for the pixels of the opticalimage based on the range matrix. To determine range values for thepixels of the optical image, processing system 106 correlates the datapoints in the range matrix with the pixels in the optical image. In oneembodiment, optical camera 102 and ranging device 104 are co-locatedsuch that each device has an identical field of view at an identicalangle. In another embodiment, optical camera 102 and ranging device 104are mounted adjacent to one another. This results in each devicecapturing scene 108 from a slightly different angle. Regardless of therelative location of optical camera 102 and ranging device 104, thefollowing process may be used to correlate the pixels in the opticalimage with the data points in the range matrix.

The correlation between the range matrix and the optical image is a datapoint to pixel correlation that is based on an initial correlation ofoptical camera 102 and ranging device 104. To initially correlateoptical camera 102 and ranging device 104, information captured by eachdevice is compared to determine which data points of ranging device 104correspond to which pixels in an image from optical camera 102. Forexample, in one embodiment, both optical camera 102 and ranging device104 are mounted in a fixed location such that the field of view of eachdevice overlaps. Then, portions (or all) of the information from eachdevice are compared. In one embodiment, a checkerboard pattern is placedwithin the portion of the field of view of each device that overlaps forcomparison of the images. The checkerboard pattern comprises a grid ofsquares which alternate light and dark in color. This pattern is readilyrecognizable in both the optical image from camera 102 and the intensitymatrix from ranging device 104. Optical camera 102 and ranging device104 each capture an image of the checkerboard pattern. As mentionedabove, along with the range matrix, ranging device 104 captures a lightintensity matrix comprising a plurality of data points which representlight intensity data.

From the light intensity matrix of ranging device 104 the checkerboardpattern can be ascertained. The position and location of thecheckerboard pattern within the light intensity matrix is then comparedwith the position and location of the checkerboard pattern within theoptical image captured by optical camera 102. In this way it is thendetermined which pixels of the optical image match up with which datapoints of the intensity matrix. This initial correlation (for the givenposition of optical camera 102 and ranging device 104) determines whichdata points within the intensity matrix corresponds to which pixel orpixels within the optical image. Since the intensity matrix and theoptical image may have different resolutions or may not be positioned inexact alignment, data points from the intensity matrix may beextrapolated and averaged over several pixels in the optical image.Thus, a single intensity data point may be matched to multiple pixels inthe optical image. Furthermore, a single pixel within the optical imagemay be matched to an average of neighboring intensity data points.Although in this embodiment a checkerboard pattern was used to comparethe images in other embodiments, other patterns or the like are used,including, but not limited to lines or other shape outlines.

Once the initial correlation between the optical image and the intensitymatrix is completed, the correlation between the optical image and therange matrix is determined. Correlation between the optical image andthe range matrix is the same correlation as between the optical imageand the intensity matrix, because the data points in the range matrixare aligned with the data points in the intensity matrix.

In one embodiment, the initial correlation is performed when opticalcamera 102 and ranging device 104 are initially mounted and aligned.Here, a correlation between optical camera 102 and ranging device 104may be used to improve the alignment between optical camera 102 andranging device 104. To mount and align optical camera 102 and rangingdevice 104, an initial alignment is performed such that ranging device104 and optical camera 102 generally have the same field of view. Then acorrelation between an optical image of the checkerboard and anintensity matrix of the checkerboard is performed. Once the data pointsof the intensity matrix and the optical image are compared, opticalcamera 102 and ranging device 104 may be repositioned if improvedalignment is desired. Then the correlation using the checkerboardpattern is completed again to re-correlate the optical image with theintensity matrix. The compare, re-align, and correlate cycle can becompleted as many times as necessary to achieve the desired alignmentbetween optical camera 102 and ranging device 104. In other embodiments,other procedures may be used to align optical camera 102 and rangingdevice 104.

In any case, once the initial correlation between the optical image andthe range matrix is known for a fixed location of optical camera 102with respect to ranging device 104, processing system 106 uses theinitial correlation to determine a range value for each pixel within theoptical image. Using the data point-to-pixel mapping from the initialcorrelation, processing system 106 assigns one or more range values fromthe range matrix and to each pixel the optical image. The combination ofinformation generated by assigning a range value to each pixel withinthe optical image is referred to herein as a 3D point cloud.

In one embodiment, the process of assigning range values for each pixelis made more robust by performing range and optical image analysis overa series of range matrix and optical images captured of the same scene.

Referring now to FIG. 3A, one embodiment of a method 300 for producing anew optical image at a different perspective than an original opticalimage is shown. Method 300 uses imaging system 100 to produce the newoptical image. The new optical image is a fabricated 2-dimensionaloptical image that is based on an original optical image captured byimaging system 100. Method 300 begins with the combined optical imageand range values from block 206 of method 200. The combination of therange values and optical image are used to create a new image from adifferent perspective than the original image captured by optical camera102. As used herein, a different perspective means that the new image isproduced as if optical camera 102 where at a different angle relative tothe scene than the actual angle in which optical camera 102 captured theoriginal image. In other words, a line of sight between the hypotheticallocation of a camera for the new image and the scene is different thanthe line of sight between the camera and the scene for the originalimage.

Method 300 begins at block 302 where a 3-dimensional point cloud for ascene is captured by imaging system 100. The 3-dimensional point cloudis captured as described with respect to method 200 above. FIG. 4Aillustrates one embodiment of an original image 402 captured by imagingsystem 100 of scene 404. Imaging system 100 captures an optical image402 of scene 404. Imaging system 100 also captures range information forscene 402. Lines 406 illustrate ranging signals sent from imaging system100 to objects within scene 404. As described above, the ranging datareceived is combined with the image captured to produce a 3D point cloudfor scene 404.

Next, at block 304 imaging system 100 determines what the perspective ofscene 404 will be in the newly created image. For example, FIG. 4Billustrates an example embodiment of scene 404 as hypotheticallycaptured by imaging system 100 from a new perspective. The newperspective of scene 404 is provided to image system 100 from an outsideprogram to, for example, illustrate scene 404 to another user at adifferent angle as explained below.

At block 306, imaging system 100 determines how the new perspective forthe hypothetical image of scene 404 from the new perspective willappear. Imaging system determines the appearance of the hypotheticalimage based on the original 3D point cloud. From the original 3D pointcloud, imaging system 100 calculates what the original 3D point cloudwould look like from the new perspective.

Once imaging system 100 determines what the new 3D point cloud wouldappear as in a 2D image from the new perspective, at block 308, imagingsystem 100 distorts the original image such that features have a shapeas would be expected from the new perspective. For example, opticalimage 402 is an original 2D image. FIG. 4B illustrates a newlyfabricated image 408 of scene 404 from a new, hypothetical, perspective.Scene 404 comprises a rectilinear shaped feature 410 and an ellipticalfeature 412. From the perspective of imaging system 100 in FIG. 4A, anoptical camera captures optical image 402 of scene 404. Lines 414 inFIG. 4B illustrate how ranging signals and light to/from imaging system100 would capture scene 404 if imaging system 100 were placed in thehypothetical new perspective. From the new perspective it is evidentthat rectilinear feature 410 is touched by four rays on the front facefrom the original perspective shown in FIG. 1. From the new perspective,however, rectilinear feature 410 is touched by five rays on the frontface. Thus, rectilinear feature 414 is wider in image 408 than in image402. Similarly, elliptical feature 412 has a slightly different shapefrom the new perspective as shown in image 408. Additionally, from thenew perspective the space between rectilinear feature 410 and ellipticalfeature 412 has been reduced. Again as illustrated by the space betweenthe lines 406 that contact features 410, 412 from the originalperspective and the space between the lines 414 that contact features410, 412 from the new perspective, the space between features 410, 412is reduced in new image 408.

Due to the distortion and potentially unknown data from the newperspective of new image 408, there may be errors within new image 408.These errors may appear as visual distortions in new image 408 ascompared to an actual original image from the perspective shown in FIG.4B. The smaller the change in angle from the original perspective to thenew perspective the less estimation that is needed and the lesspotential for distortion in the new image. In contrast, large changes inperspective require larger amounts of estimation and can cause largedistortions in the new image. Due to the resulting distortion there maybe situations in which the angle of change between the originalperspective and the new perspective is limited based on the particularapplication for new image 408.

Producing a new image from a different perspective based on an originaloptical image and a range imaging can have many applications. Forexample, in one embodiment, an image captured from one perspective canbe converted to an image as would have been captured from anotherperspective to aid in identifying objects or places.

In one embodiment, imaging system 100 and methods 200 and 300 are usedto create a 3-dimensional optical image. As used herein, a 3-dimensionaloptical image refers to two 2D optical images of a single scene from twodifferent perspectives, wherein the perspectives are approximately adistance between a viewer's eyes apart. This is sometimes referred to asa stereo vision image, and is an attempt to better replicate the humanvision experience of viewing the world from two perspectivessimultaneously (a left eye perspective and a right eye perspective).

Here, a first image of a scene is captured from a first perspective withimaging system 100. Then, a second image of the scene is created from asecond perspective in the manner described in methods 200 and 300. Inone embodiment, the second perspective is approximately an eye distanceaway from the first perspective. This second image is then used for asthe view from one of the viewer's eyes and the first image is used asthe view from the other of the viewer's eyes. The combination of the two2D optical images creates a 3D optical image. In another embodiment, thesecond perspective is a larger distance away from the first perspective(e.g. 10 degrees). Then, a third new image of the scene is created fromthe third perspective in the manner described in methods 200 and 300.The third perspective is approximately an eye distance away from thefirst perspective. The 3D image is then created from the second imageand the third image. Thus, the second image is then used as the viewfrom one of the viewer's eyes and the third image is used as the viewfrom the other of the viewer's eyes.

Methods 200 and 300 may be applied in a video by repeating the steps ofmethods 200 and 300 for each frame of a frame-by-frame video. Each frameof the frame-by-frame video is captured with imaging system 100 andprocessed through the steps of methods 200 and 300. The resulting newframes are then shown in a frame-by-frame manner for the new video.

Another application for methods 200 and 300 includes producing a videoor portions of a video from a perspective different from the perspectivethat the video was originally shot. Here, the video may be shot from oneperspective with imaging system 100, and during editing portions of thevideo may be modified to be shown from a different perspective withouthaving to re-shoot the particular scenes.

Additionally, in one embodiment, imaging system 100 and methods 200 and300 are used to create a 3D video. Here, the video is filmed from asingle perspective with imaging system 100. Then, one or two additionalperspectives may be created and used for the left eye and right eyeimages in the 3D video. For example, the video may be filmed from aperspective that is the desired center point between the left and righteyes of the viewer. Then two new images may be created based on theoriginal image. One image is slightly to the right of the filmed imageand the other image is slightly to the left of the filmed image.Advantageously, this method of producing a 3D video produces two imageswith little distortion because the perspective change for both the leftand the right image from the center filmed image is small. In anotherembodiment, the filmed image is used as one eye and a new image iscreated for the other eye. Thus, in this embodiment only one new imageis created to create the 3D video.

Referring now to FIG. 3B, one embodiment of another method 301 is shown.In method 301 the combination of the range information and the opticalimage is used for feature recognition. Blocks 202-206 of method 200precede blocks 302-304 where at block 309 a 3D point cloud for a sceneis captured. Then, the feature recognition shown in blocks 310-312occurs. In one embodiment processing system 106 has a priori knowledgeof the 3D shapes of features. At block 310, processing system 106 thenuses the determined 3D shapes for features within optical image 402 andcompares the 3D shapes to known features in an attempt at featurerecognition. This method may be done in conjunction with a standardfeature recognition algorithm or without a standard feature recognitionalgorithm. In addition to (or instead of) comparison of the 3D shapes,at block 312, processing system 106 uses the orientation of faces withinthe optical image as determined at block 304, and compares theorientation of the faces with a priori knowledge about the orientationof faces of known features. For example, a known feature may comprise asquare face on one component which is at approximately a 45 degree anglerelative to a cylindrical component and half of the size of thecylindrical component. The feature recognition algorithm then looks forthis type of 3-dimensional feature within an optical image in an attemptto find a match within the optical image.

Although specific embodiments have been illustrated and describedherein, it will be appreciated by those of ordinary skill in the artthat any arrangement, which is calculated to achieve the same purpose,may be substituted for the specific embodiments shown. It is manifestlyintended that any inventions be limited only by the claims and theequivalents thereof.

1. A method for combining range information with an optical imagecomprising: capturing a first optical image of a scene with an opticalcamera, the first optical image comprising a plurality of pixels;capturing range information of the scene with a ranging device; anddetermining range values for at least a portion of the plurality ofpixels of the first optical image based on the range information;combining the range values and the first optical image to produce a3-dimensional (3D) point cloud; and producing a second optical image ofthe scene from a different perspective than the first optical imagebased on the 3D point cloud.
 2. The method of claim 1, furthercomprising: creating a 3-dimensional (3D) optical image from the firstoptical image and the second optical image.
 3. The method of claim 1,further comprising: producing a third optical image of the scene from athird perspective; and creating a 3-dimensional (3D) optical image fromthe second optical image and the third optical image.
 4. The method ofclaim 1, wherein the first optical image is captured from a perspectiveof a first user, the method further comprising: displaying the secondoptical image to a second user, wherein the second optical image isproduced from a perspective of the second user.
 5. The method of claim1, wherein the optical image is an image that captures a visual spectrumof light that is reflected off of objects within the scene.
 6. Themethod of claim 1, wherein the ranging device is selected from a groupconsisting of: a LIDAR, a RADAR, a SONAR, a time of flight camera, and aDOPPLER.
 7. An imaging system comprising: a processing system having aprogrammable processor and a storage medium; an optical cameracommunicatively coupled to the processing system; and a ranging devicecommunicatively coupled to the processing system; wherein the opticalcamera and the ranging device are oriented such that the field of viewof the optical camera is substantially the same as the field of view ofthe ranging device; wherein the processing system is configured toproduce a new optical image of a different perspective than an originaloptical image captured by the optical camera based on the originaloptical image captured by the optical camera and range informationcaptured by the ranging device.
 8. The system of claim 7, wherein theprocessing system is further configured to create a 3-dimensional (3D)image with the original optical image and the new optical image.
 9. Thesystem of claim 7, wherein the processing system is further configuredto produce a second new optical image of the scene from a thirdperspective; and create a 3-dimensional (3D) optical image from the newoptical image and the second new optical image.
 10. The system of claim7, wherein the processing system is further configured to combine therange values and optical image to produce a 3-dimensional point cloud.11. The system of claim 7, wherein the optical camera is configured tocapture an optical image of a visual spectrum of light that is reflectedoff of objects within the scene.
 12. The system of claim 7, wherein theranging device is selected from a group consisting of: a LIDAR, a RADAR,a SONAR, a time of flight camera, and a DOPPLER.
 13. The system of claim7, further comprising a display device communicatively coupled to theprocessing system and remote from the processing system, wherein theoriginal optical image is captured from a perspective of a first user,and the display device is configure to display the new optical image toa second user, wherein the new optical image is produced from aperspective of the second user.
 14. A method for feature recognitioncomprising: capturing an optical image of a scene with an opticalcamera, the first optical image comprising a plurality of pixels;capturing range information of the scene with a ranging device;determining range values for at least a portion of the plurality ofpixels of the optical image based on data from the ranging information;and comparing the range information to known 3-dimensional features todetermine if any of the known 3-dimensional features match the ranginginformation.
 15. The method of claim 14, wherein comparing the ranginginformation compares a combination of the range information and theoptical image with known 3-dimensional data for features.
 16. The methodof claim 14, wherein the ranging device is selected from a groupconsisting of: a LIDAR, a RADAR, a SONAR, a time of flight camera, and aDOPPLER.
 17. The method of claim 14, further comprising: determining anorientation of at least one face of a feature within the optical image;and comparing the orientation of the at least one face with known faceorientations to determine if any of the known face orientations matchwith the determined orientation of the at least one face.
 18. The methodof claim 14, further comprising: performing an optical featurerecognition on the optical image using known optical representations offeatures; and determining an feature match based on the optical image;and verifying the optical feature match by comparing ranging informationcaptured for the feature image to ranging information known regardingthe feature.
 19. The method of claim 14, wherein the optical image is animage that captures a visual spectrum of light that is reflected off ofobjects within the scene.
 20. The method of claim 1, wherein the firstoptical image and the range information are captured at substantiallythe same time.